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In the realm of generative AI, open-source technologies are becoming more crucial. This week, the Linux Foundation hosted its AI dot dev event to highlight its significance in the generative AI age. The Linux Foundation oversees various open-source initiatives, including the Cloud Native Computing Foundation (CNCF), the PyTorch Foundation, and the LF AI and Data project. One of the newest initiatives, Generative AI Commons, was quietly launched in September and has been growing, adding new members and setting its direction at this event.
Jim Zemlin, executive director of the Linux Foundation, highlighted the importance of open-source for technological innovation during the event’s opening keynote, emphasizing that “open innovation” is a fundamental freedom of expression.
The Linux Foundation’s research group conducted a survey to better understand the adoption of generative AI in enterprises. According to Zemlin, “The world is rapidly adopting generative AI tools, and half of the organizations we talked to are already using them.” However, security and data privacy concerns are the main barriers. The survey also found that most organizations prefer open-source generative AI technologies over proprietary ones. Zemlin noted that open AI can help in understanding how models work, which is crucial for transparency, trust, and competition.
Matt White, director of the Generative AI Commons, gave a keynote on the project’s goals, progress, and future plans. The initiative now boasts over 100 active members and aims to promote ethical open-source generative AI innovations. White emphasized that the Commons is about ensuring AI benefits are widespread and knowledge is shared, keeping AI’s future in the hands of many rather than a select few.
The Generative AI Commons is divided into four main work streams: model and data, frameworks, applications, and education. They are currently working on the model openness framework, which assesses generative AI projects based on open science and open-source principles. White noted that the group plans to expand its hosted projects, including models, datasets, and applications, all within a strongly governed, responsible AI community.